Three-dimensional information processing apparatus and method

ABSTRACT

A three-dimensional information processing apparatus for obtaining three-dimensional information from an object having a three-dimensional shape, and performing predetermined information processing, comprises: a camera for sensing images of the object from a plurality of coordinate positions using an image sensing system having one or a plurality of optical systems. A plurality of depth information are extracted from image sensing related information sensed by the camera at the plurality of coordinate positions, and the plurality of extracted depth information are converted and unified into depth information expressed by a unified coordinate system.

This is divisional of co-pending application Ser. No. 08/885,823, filedJun. 30, 1997 and now U.S. Pat. No. 6,445,814.

BACKGROUND OF THE INVENTION

The present invention relates to a three-dimensional informationprocessing apparatus and method for extracting three-dimensionalinformation, that can be used in CG, CAD, and the like, from an objecthaving a three-dimensional shape.

As a conventional technique for obtaining the three-dimensional shape ofan object, for example, “Stereoscopic matching using a plurality of baseline distances” (Journal of Papers of the Institute of Electronics,Information and Communication Engineers D-II, Vol. J75-D-II, No. 8, pp.1317-1327, August 1992) is known. Generally, the conventional method ofacquiring a three-dimensional shape can be roughly classified intopassive and active methods.

One typical passive method is a stereoscopic image method, whichutilizes trigonometric measurements using two cameras. In this method,the positions of images of an identical object are detected from rightand left images taken by cameras, and the three-dimensional position ofthe object is measured based on the displacement amount between thedetected positions.

As typical active methods, an optical radar type range finder whichobtains distance by measuring the time until light projected toward andreflected by an object returns, a slit light projection method forprojecting a slit-shaped light pattern onto an object, and measuring thethree-dimensional shape on the basis of the displacement of the patternshape formed on the object, and the like are known.

Note that the three-dimensional data of the object obtained by theabove-mentioned methods can be reproduced and displayed on, e.g., atwo-dimensional display.

However, the stereoscopic image method has as its major objective tocalculate the distance information from a specific position where thecameras are set to the object, and does not measure thethree-dimensional shape itself of a certain object. In the activemethods, since a laser beam or the like must be irradiated onto theobject, it is cumbersome to use such methods.

For this reason, such methods cannot flexibly cope with a dynamic imagesensing environment, i.e., image sensing while moving around a certainobject, and hence, none of the conventional methods can extract depthinformation in such dynamic image sensing environment.

Images normally used in an office are often finally output onto papersheets, and images types to be used include both natural images and lineimages that express objects by edge lines alone. More specifically, inan office or the like, it is a common practice to process imageinformation for various purposes.

In contrast to this, since the principal object of the above-mentionedprior art is to calculate the three-dimensional shape data of the objectfrom certain specific setting positions of the cameras and to faithfullydisplay the calculated data on a two-dimensional display, theabove-mentioned methods cannot cope with various kinds of imageprocessing required in, e.g., an office.

More specifically, the present invention is addressed to athree-dimensional information extraction apparatus which can be easilyapplied to a dynamic image sensing environment in which the imagesensing position changes, and can process acquired three-dimensionalinformation into various forms.

Some stereoscopic image processing apparatuses use three or more imagesin place of two images, and form three-dimensional shapes by unifyingshape information obtained from such images.

Upon judging the reliability of the obtained three-dimensional shape,for example, the above-mentioned stereoscopic image method uses thecomparison result or correlation of residuals obtained upon calculatingthe position displacement amount by corresponding point extraction ofthe luminance values in place of reliability judgment.

However, in the above-mentioned prior arts, in the case of, e.g., thestereoscopic image method, even when the residual is large or when thecorrelation function is small, if the angle the object makes with theimage sensing plane is large or the distance from the apparatus to theobject is large, calculation errors due to minimum errors of thecorresponding extraction results are large, and the obtainedthree-dimensional shape has low reliability. On the other hand, theobtained three-dimensional shape is not displayed considering its lowreliability.

That is, the present invention is also addressed to improvement ofreliability in three-dimensional information processing.

On the other hand, the present invention is addressed to storage ofimage information in the dynamic image sensing environment. Problemsassociated with storage of image information in the dynamic imagesensing environment will be discussed below.

In a certain prior art associated with the dynamic image sensingenvironment, a single image sensing unit placed on a rail is translatedto sense a plurality of images, and shape analysis is made using thecorrelation among the sensed images.

In addition, Japanese Patent Publication No. 7-9673 is known as thetechnique of analyzing the shape of a stereoscopic object using thecorrelation among two pairs of parallax images sensed at the same timeusing a compound-eye image sensing device which is made up of aplurality of image sensing units. In this prior art, the image sensingdevice is fixed to a robot arm, and is moved as instructed to senseimages.

A conventional image sensing apparatus which allows the photographer tofreely carry the image sensing apparatus main body and can analyze theshape of an arbitrary object will be described below.

FIG. 1 is a block diagram showing the arrangement of a conventionalportable automatic image sensing apparatus and the principle of its usestate.

In FIG. 1, reference numeral 1101 denotes an object to be sensed (a cupin this embodiment), which is placed on a pad 1102, and a case will beexplained below wherein this object 1101 is to be sensed. A plurality ofbright point marks 1103 a, 1103 b, and 1103 c are printed on the pad1102, and their position relationship is known and is pre-stored in animage sensing apparatus 1900 (to be described below).

Reference numeral 1900 denotes a portable image sensing apparatus, whichcomprises photographing lenses 1110 and 1111, shutters 1112 and 1113which also serve as iris diaphragms, image sensing elements 1114 and1115 for performing photoelectric conversion, control circuits 1116 and1117 for controlling the image sensing elements 1114 and 1115, imagesignal processing circuits 1118 and 1119 for processing signals obtainedfrom the image sensing elements 1114 and 1115, image signal storagecircuits 1120 and 1121 for storing image signals output from the imagesignal processing circuits 1118 and 1119, a corresponding pointextraction circuit 1122, an image sensing parameter detection circuit1123, a ROM (read-only memory) 1124 that stores the (known) positionrelationship among the bright points on the pad, a unifying circuit 1125for unifying three-dimensional information, and buffer circuits 1126 and1127 for temporarily storing the three-dimensional information unifiedby the three-dimensional information unifying circuit 1125.

This image sensing apparatus 1900 extracts corresponding points from theobtained two image signals by the corresponding point extraction circuit1122 to obtain distance images at the individual timings, and at thesame time, obtains image sensing parameters (the position relationshipbetween the pad and the image sensing apparatus 1900 obtained based onthe bright point coordinate positions, accurate focal length, and thelike) using the image sensing parameter detection circuit 1123 and theROM 1124. The three-dimensional information unifying circuit 1125calculates three-dimensional shape data and texture image data of theobject 1101 on the basis of these distance images, image sensingparameters, and change information that expresses their time-serieschanges, and stores them in the buffer circuits 1126 and 1127.

In FIG. 1, reference numeral 1140 denotes numerical value data of thethree-dimensional shape of the object 1101 output from the image sensingapparatus 1900; and 1141, developed image data of the surface texture ofthe object 1101. These output data are transferred to a personalcomputer or the like, which performs texture mapping to display theinput data as a stereoscopic CG (computer graphics) image. The displayangle, size, and the like of the CG image can be instantaneouslychanged, and the image can also be deformed and processed. Two CG imageswhich have slightly different view points are generated, and are outputto a stereoscopic display, thus allowing the user to observe astereoscopic image. In this case, since the stereoscopic image can befreely rotated and deformed, the user can experience higher reality.

In the image sensing apparatus 1900, the corresponding point extractioncircuit 1122 and the three-dimensional information unifying circuit 1125require the most complicated, time-consuming processing and, hence,require a very large circuit scale and consumption power. The imagesensing apparatus 1900 has a sequential processing mode in which suchcomplicated processing is sequentially executed while sensing images,and a simultaneous processing mode in which the required sensed imagesare stored in the image signal storage circuits 1120 and 1121, andthereafter, the processing is executed simultaneously. On the otherhand, the image sensing apparatus 1900 allows the photographer to freelycarry the image sensing apparatus 1900 without requiring any large-scalepositioning device unlike in the above-mentioned prior art, and caneasily analyze the shape of the object 1101 without requiring anyspecial preparation processes.

However, the prior art shown in FIG. 1 suffers the following problems.

More specifically, in general, accurate positioning cannot be attainedat a constant speed even by the operation of the photographer unlike inthe above-mentioned conventional positioning device. For example, whenimages are stored in the image storage circuit at given time intervalsand are subjected to image processing, redundant information increasesin a portion sensed by moving the apparatus at an excessively low speed,and a very large image memory capacity is required, resulting in a longshape analysis time. Furthermore, the analyzed three-dimensional shapedata becomes excessively fine, and the subsequent CG generation requiresan extra processing time and storage capacity. Conversely, when thephotographer moves the image sensing apparatus at high speed,information required for analyzing the three-dimensional shape becomesshort, and the analysis precision is impaired. In the worst case, if animage of a specific side surface of the object cannot be acquired, theshape information of that portion is lost.

SUMMARY OF THE INVENTION

The present invention has been made in consideration of the abovesituation, and has as its object to provide a three-dimensionalinformation processing apparatus and method, which can flexibly copewith dynamic image sensing, and can process the obtainedthree-dimensional information into various forms.

In order to achieve the above object, according to the presentinvention, there is provided a three-dimensional information processingapparatus for obtaining three-dimensional information from an objecthaving a three-dimensional shape, and performing predeterminedinformation processing, comprising:

image sensing means for sensing images of the object from a plurality ofcoordinate positions using an image sensing system having one or aplurality of optical systems;

information extraction means for extracting a plurality of depthinformation from image sensing related information sensed by the imagesensing means at the plurality of coordinate positions; and

conversion/unification means for converting and unifying the pluralityof depth information extracted by the depth information extraction meansinto depth information expressed by a unified coordinate system.

Also, in order to achieve the above object, according to the presentinvention, there is provided a three-dimensional information processingmethod for obtaining three-dimensional information from an object havinga three-dimensional shape, and performing predetermined informationprocessing, comprising:

the first step of sensing images of the object from a plurality ofcoordinate positions using an image sensing system having one or aplurality of optical systems;

the second step of extracting a plurality of depth information fromimage sensing related information sensed at the plurality of coordinatepositions in the first step; and

the third step of converting and unifying the plurality of depthinformation extracted by the depth information extraction means intodepth information expressed by a unified coordinate system.

According to the apparatus and method with the above arrangement, uponunifying depth information, since a plurality of depth information areconverted into depth information expressed by a unified coordinatesystem on the basis of, e.g., the luminance information of the objectand displacement information of distance information, the presentinvention can flexibly cope with dynamic image sensing in which imagesensing is done while moving the apparatus around a certain object, andcan easily process the obtained information into various image forms.

According to one preferred aspect of the present invention, adisplacement between coordinate systems of the plurality of depthinformation is detected on the basis of the image information of theobject.

According to one preferred aspect of the present invention, the unifiedcoordinate system has five different projection planes.

According to one preferred aspect of the present invention, the imageinformation includes luminance information of the object, and thedisplacement between the coordinate systems is detected on the basis ofthe luminance information.

In order to achieve the above object, according to the presentinvention, there is provided a three-dimensional information processingapparatus for obtaining three-dimensional information from an objecthaving a three-dimensional shape, and performing predeterminedinformation processing, comprising:

image sensing means for sensing images of the object using an imagesensing system having one or a plurality of optical systems;

three-dimensional shape extraction means for extractingthree-dimensional shape information of the object from image sensingrelated information sensed by the image sensing means; and

reliability determination means for determining reliability of thethree-dimensional shape information extracted by the three-dimensionalshape extraction means.

It is another object of the present invention to provide athree-dimensional information processing apparatus and method, which cannotify the discrimination result of reliability.

It is still another object of the present invention to provide athree-dimensional information processing apparatus and method, which canprocess three-dimensional shape information in accordance with thediscrimination result of reliability, and can display the processedthree-dimensional shape information.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of an angle of the object with respect to an image sensingplane.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of a distance between the image sensing means and the object.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of an angle a pad that places the object thereon makes with animage sensing plane of the image sensing means.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of an area ratio of a pad that places the object thereon to animage sensing region.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of a position of a pad that places the object thereon.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of reflected light information reflected by the object.

According to one preferred aspect of the present invention, thereliability of the three-dimensional shape information is determined onthe basis of a degree of correspondence of pixels between a plurality ofimage sensing related data sensed by the image sensing means.

It is still another object of the present invention to provide an imagesensing method and apparatus, which can minimize the storage capacity ofstorage means that stores images, can shorten the time required forprocessing images, and can avoid any errors upon executing processing ordisplay after image sensing.

In order to achieve the above object, according to the presentinvention, there is provided an image sensing method comprising:

the image sensing step of sensing images of an object;

the storage step of storing image information of the object;

the image sensing condition detection step of detecting a relativerelationship between the object and an image sensing apparatus mainbody; and

the control step of controlling a storage operation of the imageinformation,

wherein the control step includes the step of controlling the storageoperation in the storage step in accordance with a detection result ofthe image sensing condition detection step.

Also, in order to achieve the above object, according to the presentinvention, there is provided an image sensing apparatus comprising:

image sensing means for sensing images of an object;

storage means for storing image information of the object;

image sensing condition detection means for detecting a relativerelationship between the object and an image sensing apparatus mainbody; and

control means for controlling the storage means,

wherein the control means controls the storage means in accordance withan output from the image sensing condition detection means.

According to the method or apparatus with the above arrangement, sincethe required minimum capacity of images used in image display andthree-dimensional shape analysis is always stored, the storage capacityof the storage means can be reduced, and the operation time of thethree-dimensional shape analysis processing means can be shortened,thereby realizing a size reduction and a cost reduction of the overallapparatus.

In order to achieve the above object, according to the presentinvention, there is provided an image sensing method comprising:

the image sensing step of sensing images of an object;

the analysis step of analyzing image information obtained in the imagesensing step;

the image sensing condition detection step of detecting a relativerelationship between the object and an image sensing apparatus mainbody; and

the control step of controlling an image analysis operation in theanalysis step,

wherein the control step includes the step of controlling the imageanalysis operation in accordance with a detection result of the imagesensing condition detection step.

Also, in order to achieve the above object, according to the presentinvention, there is provided an image sensing apparatus comprising:

image sensing means for sensing images of an object;

image analysis means for analyzing image information sensed by the imagesensing means;

image sensing condition detection means for detecting a relativerelationship between the object and an image sensing apparatus mainbody; and

control means for controlling the image analysis means,

wherein the control means controls the image analysis means inaccordance with an output from the image sensing condition detectionmeans.

According to the image sensing method and apparatus with the abovearrangement, since required minimum images alone are subjected tothree-dimensional shape analysis processing, the operation time of thethree-dimensional analysis can be shortened, and loss of required imagescan be avoided, thus realizing a size reduction and a cost reduction ofthe overall apparatus.

According to one preferred aspect of the present invention, control ismade to store information associated with the relative relationshipbetween the object and the image sensing apparatus main body togetherwith sensed images sensed in the image sensing step in the storage step.The stored information can be easily compared with desired observationdirection information input by the observer upon reproduction of animage, and an appropriate image can be instantaneously displayed.

According to one preferred aspect of the present invention, the imagesensing condition is detected using a sensor for detecting an angle andtranslation movement of the image sensing apparatus main body. Samplingpositions can be assigned on the space at nearly equal intervals by asimple apparatus arrangement.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of analyzing an objectimage and images around the object sensed by the image sensing apparatusmain body, and detecting an angle and translation movement of the imagesensing apparatus main body on the basis of changes in state of sensedimages sensed in the image sensing step. The sampling interval of imagescan be appropriately changed in correspondence with the complexity ofthe object structure.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of analyzing an objectimage and images around the object sensed by the image sensing apparatusmain body, and detecting changes in relative position relationshipbetween the object and the image sensing apparatus main body on thebasis of an error signal generated upon analyzing the images. Since theshape information of the object region that could not be analyzed at acertain time can be compensated for using information obtained byanalyzing an image at a different time, accurate three-dimensional shapedata can always be output.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of analyzing an objectimage sensed by the image sensing apparatus main body, and detectingchanges in occlusion state of the object. Even for an object with acomplicated shape, regions that cannot be analyzed are few, and accurateinformation can be output as a whole.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of analyzing an objectimage sensed by the image sensing apparatus main body, and detecting anoverlapping region area between time-serial object images. Inparticular, when high-magnification image sensing is done, jointanalysis between images can be performed from images with predeterminedprecision, and loss of required images can be avoided.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of analyzing an objectimage sensed by the image sensing apparatus main body, and detectingchanges in distance image of the object. In the object regioncorresponding to a complicated three-dimensional shape, the number oftimes of sampling can be increased, and high-precision three-dimensionalshape data can be output.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of analyzing an objectimage sensed by the image sensing apparatus main body, and detectingchanges in distance image of the object. In the object regioncorresponding to a complicated three-dimensional shape, the number oftimes of sampling can be increased, and high-precision three-dimensionalshape data can be output.

According to one preferred aspect of the present invention, the imagesensing condition detection includes the step of stopping the imagesensing step and the analysis step during a period in which neitherstorage processing nor analysis processing are performed. Since theimage sensing means and the image analysis means that consume relativelylarge power cease to operate during the period that requires neitherimage storage nor processing, consumption power can be greatly reduced.

According to one preferred aspect of the present invention, the imageanalysis step includes the step of performing an analysis calculationfor acquiring a three-dimensional shape and a surface image of theobject using a plurality of images. Accordingly, since an object imageis generated using texture mapping or the like in computer graphics, theobserver can freely select the observation direction and distance, andthe three-dimensional shape and surface state.

Other features and advantages of the present invention will be apparentfrom the following description taken in conjunction with theaccompanying drawings, in which like reference characters designate thesame or similar parts throughout the figures thereof.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic block diagram showing the arrangement of aconventional three-dimensional information processing apparatus;

FIG. 2 is a schematic block diagram showing the arrangement of athree-dimensional information processing apparatus according to thefirst embodiment of the present invention;

FIGS. 3A and 3B are block diagrams showing the arrangement of athree-dimensional shape extractor 12 in detail;

FIG. 4 is a block diagram showing the arrangement of a system controller210 in detail;

FIG. 5 is a block diagram showing the portion associated with extractionof depth information;

FIG. 6 is a block diagram showing the portion associated withunification of depth information;

FIG. 7 is an explanatory view of template matching;

FIGS. 8A and 8B are explanatory views for explaining the procedure ofunifying depth information;

FIGS. 9A and 9B are explanatory views for explaining the procedure ofunifying depth information;

FIGS. 10A and 10B are explanatory views for explaining the procedure ofunifying depth information;

FIG. 11 is a schematic view showing the intermediate point interpolationmethod;

FIG. 12 is a view showing the method of converting depth informationinto one expressed by a unified coordinate system;

FIG. 13 is a view showing the method of converting depth informationinto one expressed by the unified coordinate system;

FIG. 14 is a block diagram showing the arrangement associated withextraction of distance information according to the second embodiment ofthe present invention;

FIG. 15 is a block diagram showing the arrangement associated withunification of distance information;

FIG. 16 is a flow chart showing the operation of an image sensing headdevice 1;

FIG. 17 is an explanatory view of zoom adjustment;

FIG. 18 is an explanatory view of zoom adjustment;

FIG. 19 is an explanatory view of reliability discrimination;

FIG. 20 is an explanatory view of reliability discrimination;

FIG. 21 is an explanatory view of a three-dimensional informationprocessing apparatus according to the third modification of the secondembodiment;

FIG. 22 is a block diagram showing the arrangement of athree-dimensional shape extractor 12 according to the third modificationin detail;

FIG. 23 is a flow chart showing the operation of an image sensing headdevice 1 according to the third modification;

FIG. 24 is an explanatory view of reliability discrimination accordingto the third modification;

FIG. 25 is a block diagram showing the arrangement and use state of animage sensing apparatus according to the third embodiment of the presentinvention;

FIG. 26 is a diagram showing the arrangement of a posture sensoraccording to the third embodiment;

FIG. 27 is a diagram showing the arrangement of acceleration sensorsthat make up the position sensor of the third embodiment;

FIG. 28 is a view showing an example of the image input timings of thethird embodiment;

FIGS. 29A to 29C show examples of sensed images in the third embodiment;

FIGS. 30A to 30C show examples of sensed images in the third embodiment;

FIG. 31 is a block diagram showing the arrangement and use state of animage sensing apparatus according to the fourth modification; and

FIG. 32 is a block diagram showing the arrangement of a stereoscopicimage display means in the fourth modification.

DETAILED DESCRIPTION OF THE INVENTION

The preferred embodiments of the present invention will be described indetail hereinafter with reference to the accompanying drawings.

<First Embodiment>

The first embodiment of the present invention will be described below.

FIG. 2 is a schematic block diagram showing the arrangement of athree-dimensional information processing apparatus according to thefirst embodiment of the present invention.

Arrangement

A three-dimensional information processing system according to the firstembodiment comprises an image sensing head device 1, a three-dimensionalshape extractor 12 for extracting the three-dimensional shape from animage sensed by the head device 1, a text editor 1001 for creating textdata, a data combining unit (program) 1000 for combining image dataextracted by the extractor 12 and the data generated by an operationunit 11, a monitor 8 for displaying two-dimensional image data of anobject 2 and text data, a printer 9 for printing the two-dimensionaldata of the object 2 and text data on a paper sheet or the like, and theoperation unit 11 for moving the view point of the object 2, changingthe display format of the object 2, and attaining combining and editingof data using the data combining unit 1000.

The image sensing head device 1 senses images of the object 2 having athree-dimensional shape, which is present in front of a background plane3. The three-dimensional shape extractor 12 comprises an image sensingprocessor 13 for executing various kinds of image processing for imagessensed by the image sensing head device 1.

In the first embodiment, the user can select one of a plurality ofdisplay formats of the object 2. More specifically, the display formatsinclude, e.g., a natural image, a line image that expresses the edges ofthe object 2 by lines, a polygon image that expresses the surface of theobject 2 as contiguous planes each having a predetermined size, and thelike.

The image sensing head device 1 comprises an image sensing lens 100Rlocated on the right side when viewed from the apparatus, an imagesensing lens 100L located on the left side when viewed from theapparatus, and an illumination unit 200 that outputs illumination lightin correspondence with an image sensing environment. In FIG. 2, 10Lrepresents the image sensing range of the left image sensing lens 100L,and 10R the image sensing range of the right image sensing lens 100R.The image sensing head device 1 senses images of the object 2 whilemoving to arbitrary positions within the range from an image sensingstart position A₀ to an image sensing end position A_(n). Note that theposition information of the image sensing head unit 1 at each imagesensing position between A₀ and A_(n) is output to a posture detector 4(to be described later).

The image sensing processor 13 comprises the posture detector 4, animage memory 5, a 3D image processor 6, and a 2D image processor 7.

The posture detector 4 of the image sensing processor 13 has a positiondetector comprising a unit for calculating the position information ofthe image sensing head device 1 by image processing on the basis ofinformation obtained from the background plane 3, and a unit forcalculating the position information of the image sensing head device 1by a sensor such as a gyro or the like. With this detector, the positionof the image sensing head device 1 with respect to the background plane3 can be determined.

The image memory 5 stores image data obtained by the image sensing headdevice 1, and the position information of the image sensing head device1 obtained by the posture detector 4, and comprises an image memory 5Rfor right images, and an image memory 5L for left images.

The 3D image processor 6 calculates the three-dimensional shape (depthinformation, i.e., distance information) of the object 2 on the basis ofthe image data stored in the image memory 5 and the correspondingposition information of the image sensing head device 1.

The 2D image processor 7 calculates two-dimensional image data of theobject 2 viewed from an arbitrary view point in the image formatdesignated by the user on the basis of the stereoscopic image data ofthe object 2 obtained by the 3D image processor 6.

With the three-dimensional information processing apparatus having theabove-mentioned arrangement, when the user directs the image sensinghead device 1 toward the object 2, and operates a release button (notshown), images of the object 2 are sensed, and the first image data arestored in the image memory 5.

Subsequently, when the user moves the image sensing head device 1 froman arbitrary position A₀ to a position A_(n) to have the object 2 as thecenter, the posture detector 4 detects that the position and directionhave changed from the initial position A₀ of the image sensing head unit1 by a predetermined amount during movement from the position A₀ to theposition A_(n). After such detection is done by the posture detector 4,second image sensing is made at a position A₁, and thereafter, imagesensing is repeated n times in turn.

At this time, the image data and the displacement amounts from theinitial image sensing position and direction of the image sensing headdevice 1 obtained by the posture detector 4 are stored in the imagememory 5. When the posture detector 4 detects that at least one of themoving amount of the image sensing head device 1 and the directionchange amount has largely exceeded a predetermined value, an alarm unit(to be described later) produces an alarm.

Thereafter, this operation is repeated several times. After the imagedata sufficient for calculating the depth information of the object 2are obtained, an image sensing end information unit (not shown) informsthe user of the end of image sensing, thus ending the image sensingprocessing.

Upon completion of the image sensing processing, the 3D image processor6 calculates stereoscopic image data of the object 2 on the basis of theimage data of the object 2 and the position information of the imagesensing head device 1 corresponding to the image data, which are storedin the image memory 5. The 2D image processor 7 calculatestwo-dimensional image data viewed from the initial image sensingposition (the position A₀) of the object 2, and outputs it to themonitor 8. The image format of the image to be output to the monitor 8can be selected by the operation unit 11.

The user can display an object image viewed from an arbitrary view pointon the monitor 8 by operating the operation unit 11. For this purpose,the 2D image processor 7 generates the object image viewed from thedesignated view point by performing predetermined calculations of thestereoscopic image data in correspondence with the user's operation onthe operation unit 11. Also, the user can change the image format of theobject 2 displayed on the monitor 8 to other formats (natural image,polygon image, and the like) by operating the operation unit 11.

The user can output the sensed image of the object 2 to the printer 9after he or she changes the view point and the image format incorrespondence with his or her purpose. Furthermore, the user cancombine and edit text data created in advance and the object image datacalculated by the 2D image processor 7 using the data combining unit1000 while displaying them on the monitor 8. At that time, the user canalso change the image format and view point of the object 2 by operatingthe operation unit 11.

The detailed arrangement of the three-dimensional shape extractor 12will be described below.

FIG. 3 shows, in detail, the arrangement of the three-dimensional shapeextractor 12, i.e., the arrangement of the image sensing head device 1and the image sensing processor 13.

As shown in FIG. 3, the three-dimensional shape extractor 12 comprisesthe above-mentioned posture detector 4, image memories 73R and 73L forstoring images which are being sensed currently, image memories 75R and75L for storing images sensed at the immediately preceding image sensingtiming, an overlapping portion detector 92 for detecting the overlappingportion of the sensed images, a sound generator 97 for informing thesetting state of various image sensing parameters such as an exposurecondition and the like by means of a sound, the image sensing lenses100R and 100L each consisting of a zoom lens, iris diaphragms 101R and101L for adjusting the amounts of light coming from the image sensinglenses 100R and 100L, image sensors 102R and 102L made up of CCDs, andthe like, A/D converters 103R and 103L for analog-to-digital convertingsignals from the image sensors 102R and 102L, image signal processors104R and 104L for converting the signals from the image sensors 102R and102L into image signals, image separators 105R and 105L for separatingan object, from which three-dimensional information (depth information)is to be extracted, from the background plane 3, zoom controllers 106Rand 106L for adjusting the focal lengths of the image sensing lenses100R and 100L, focus controllers 107R and 107L for adjusting the focalpoint positions, iris diaphragm controllers 108R and 108L for adjustingthe aperture values, a system controller 210 for controlling the overallthree-dimensional shape extractor 12, an image processor 220 includingthe image memory 5, the 3D image processor 6, and the 2D image processor7 shown in FIG. 2, a release button 230 which is operated at thebeginning of image sensing, an EVF (electronic view finder) 240 fordisplaying the setting state of various image sensing parameters such asan exposure condition and the like, a recorder 250 which is connected tothe image processor 220 to record predetermined image data and the like,an R-L difference discriminator 260 for detecting signals required forR-L difference correction, a focusing state detector 270 for detectingthe focusing state, image sensor drivers 280R and 280L for controllingdriving of the image sensors 102R and 102L, and an I/F 760 to externaldevices, which allows connections with the external devices.

As shown in FIG. 4, the system controller 210 comprises a microcomputer900 for mainly performing the overall control, a memory 910 which storesa program required for the overall control, sensed image data, and thelike, and an image processing section 920 for performing predeterminedcalculation processing for the image data and the like stored in thememory 910 and the like.

The image processor 220 extracts three-dimensional information of theobject 2 from image signals obtained from the image sensing lenses 100Rand 100L, and unifies and outputs a plurality of extractedthree-dimensional information (depth information) of the object 2 at theindividual image sensing positions on the basis of a plurality ofposture information at the individual image sensing positions obtainedfrom the posture detector 4.

FIG. 5 is a block diagram showing the arrangement of the image processor220 in detail, and mainly shows the arrangement portion associated withextraction of depth information in the image processor 220.

The image processor 220 extracts depth information from stereoscopicimages 110 consisting of right and left images (R and L images) storedin the predetermined image memories.

As shown in FIG. 5, the image processor 220 comprises edge extractors111 (111R, 111L) for extracting edge images from the stereoscopic images110, a stereoscopic corresponding point extractor 112 for extracting thecorrespondence among pixels in the stereoscopic images 110, acorresponding edge extractor 113 for extracting the correspondence amongpixels in two edge images extracted by the edge extractors 111, aninconsistency eliminating unit or eliminator 114 for detectinginconsistent portions from the correspondences extracted by thestereoscopic corresponding point extractor 112 and the correspondingedge extractor 113, and eliminating the inconsistent portions, anocclusion determining unit 115 for determining the occlusion regionbased on the extracted corresponding points and an index indicating thedegree of correlation used during corresponding point extraction, e.g.,a residual, a depth information distribution processor 116 forcalculating the depth information distribution by the principle oftrigonometric measurements on the basis of the relationship among thecorresponding points, characteristic point extractors 117 (117R, 117L)for identifying characteristic points of a background plane portion, anda correction data calculation unit 118 for acquiring the image sensingparameters, posture, and movement relationship using the characteristicpoints of the background plane portion.

FIG. 6 is a block diagram showing the arrangement of the image processor220 in more detail, and mainly shows the arrangement portion associatedwith unification of depth information of the object 2 in the imageprocessor 220. Note that “unification” means conversion of images sensedat different positions to image data associated with a single unifiedcoordinate system. More specifically, “unification” is to convert aplurality of depth information of the object obtained from at least twoarbitrary positions into depth data viewed from a single coordinatesystem. Also, “unification” of this embodiment also implies coordinateinterpolation processing (to be described later).

In order to attain unification processing of depth information of theobject 2, as shown in FIG. 6, the image processor 220 comprises acoordinate system converter 121 for converting two depth informationdata (Z^(t)(i, j) and Z^(t+δt)(i, j)) 120 from a pair of stereoscopicimages 110 obtained by the individual units onto a unified coordinatesystem, a depth information unificator 122 for unifying depthinformation 120′ converted onto the unified coordinate system, and adisplay unit 124 for displaying the unified depth information.

Also, the image processor 220 comprises a unit for outputting occlusionregion information 123 to the unificator 122 and the display unit 124,and a unit for detecting the moving amount and direction of the imagesensing head device 1, and the like.

Operation

The operation of the three-dimensional information processing apparatusof the first embodiment with the above arrangement will be describedbelow.

The operation of the three-dimensional shape extractor 12 will bedescribed in detail below with reference to FIG. 3.

In the three-dimensional shape extractor 12, images of the object 2 areinput via the image sensing lenses 100R and 100L. The input objectimages are converted into electrical signals by the image sensors 102Rand 102L. Furthermore, the converted signals are converted from analogsignals into digital signals by the A/D converters 103R and 103L, andthe digital signals are supplied to the image signal processors 104R and104L.

The image signal processors 104R and 104L convert the digital signals ofthe object 2 into luminance and chrominance signals in an appropriateformat. The image separators 105R and 105L measure depth information inthe object to be sensed on the basis of the signals obtained from theimage signal processors 104R and 104L, thereby separating the principalobject 2 from the background plane 3.

As one separation method, an image of the background plane 3 is sensedin advance, and is stored in a predetermined memory. Thereafter, theprincipal object 2 is placed on the background plane, and its image issensed. The sensed image and the stored image of the background plane 3are subjected to matching and differential processing, therebyseparating the background plane region. Note that the separation methodis not limited to such specific method, and the background plane regionmay be separated on the basis of color or texture information.

The separated image data of the principal object 2 are supplied to theimage processor 220, which executes three-dimensional shape extractionprocessing on the basis of various image sensing parameters obtainedupon image sensing.

The image sensing parameters upon image sensing include, e.g., a focallength, which can be set by the following method.

Distance information Z is given by the following equation (1):$\begin{matrix}{Z = \frac{f \cdot B}{d}} & (1)\end{matrix}$

where Z: the distance, f: the focal length, B: the base line distance;and d: the parallax.

In order to precisely recognize the three-dimensional shape by imageprocessing, the resolution of the distance Z corresponding to theparallax is important. The resolution of Z is defined by the followingequation: $\begin{matrix}{\frac{\partial Z}{\partial d} = {- \frac{f \cdot B}{d^{2}}}} & (2)\end{matrix}$

Accordingly, the focal length f is written as follows using the distanceresolution determined by the parallax as a parameter: $\begin{matrix}{f = {{- \frac{d^{2}}{B}} \cdot \frac{\partial Z}{\partial d}}} & (3)\end{matrix}$

Hence, the resolution is set at, e.g., the operation unit 11 via the I/F760, and the focal length f can be set based on this value.

The method of extracting depth information Z from stereoscopic images11OR and 110L by the image processor 220 will be described below withreference to FIG. 5.

Two processing operations are done for the stereoscopic images 110R and110L read out from the predetermined image memories.

In one processing, the stereoscopic corresponding point extractor 112extracts the correspondence among pixels in the stereoscopic images 110Rand 110L on the basis of their luminance values.

In the other processing, the corresponding edge extractor 113 extractsthe correspondence among pixels in two stereoscopic edge images 110R′and 110L′ (obtained as edge images by the edge extractors 111).

The inconsistency eliminator 114 detects inconsistent portions in thecorrespondences on the basis of the outputs from the above-mentionedcorresponding point extractors (112 and 113). If the correspondenceobtained based on the luminance values does not coincide with thatobtained based on the edge images, it is determined that theirreliability is low, and it is proper to eliminate such correspondences.Alternatively, the individual correspondences may be weighted, andinconsistent portions may be detected.

The occlusion determining unit 115 determines the occlusion region onthe basis of the obtained corresponding points and an index (e.g., aresidual R) indicating the degree of correlation between correspondingpoints used during calculations of the corresponding points. Thisprocessing is to add reliability to the results of the correspondingpoint processing, although the corresponding point processing yieldstentative results. As the index indicating the degree of correlation, acorrelation coefficient or residual is used. If the residual is verylarge, or if the correlation coefficient is low, it is determined thatthe reliability of the correspondence is low. The low-reliabilityportion is processed as an occlusion region or a region without anycorrespondence.

Using the correspondence obtained via the above-mentioned processing,the depth information Z of the object 2 is calculated according toequation (1) using the principle of trigonometric measurements.

The template matching method as a typical corresponding point extractionmethod executed in the above-mentioned stereoscopic corresponding pointextractor 112 will be explained below.

In the template matching method, a template image T consisting of N*Npixels is extracted from, e.g., the image 110L obtained by the leftimage sensing system, as shown in FIG. 7. Using this template T, searchof equation (4) below is performed (M−N+1)² times in a search regionhaving a size of M×M pixels (N<M) in the image 110R obtained by theright image sensing system. That is, as shown in FIG. 7, a position (a,b) is defined as the upper left position of the template T_(L) to beset, and a residual R(a, b) given by equation (4) below is calculatedwhile placing the template T_(L) at a certain position (a, b):$\begin{matrix}{{R( {a,b} )} =  {\sum\limits_{i = 0}^{N - 1}\sum\limits_{j = 0}^{N - 1}} \middle| {{I_{R{({a,b})}}( {i,j} )} - {T_{L}( {i,j} )}} |} & (4)\end{matrix}$

This operation is repeated by moving the position (a, b) within theimage to be searched (in this example, the left image 110L) to obtain aposition (a, b) corresponding to the minimum residual R(a, b). Thecentral pixel position of the template image T_(L)(i, j) when thetemplate image T_(L)(i, j) is located at the position (a, b)corresponding to the minimum value R(a, b) is determined as acorresponding point. In the above equation, I_(R(a,b))I(i, j) representsa partial image of the right image 110R when the upper left point of thetemplate is located at the position (a, b).

The stereoscopic corresponding point extractor 112 applies the abovetemplate matching method to the stereoscopic images 110 to obtaincorresponding points for luminance level.

In corresponding point extraction for edge level, the above-mentionedtemplate matching is done for edge-extracted stereoscopic images 110L′and 110R′.

As pre-processing for corresponding point extraction for edge level, theedge extractors (111) emphasize the edge portions using, e.g., a Robertfilter or Sobel filter.

More specifically, when the Robert filter is used, the edge extractors111R and 111L receive the input images 110R and 110L (f(i, j) representseach input image), and output the output image data (g(i, j) representseach output image) expressed by the following equation:

g(i,j)=sqrt({f(i,j)−f(i+1, j+1)}²)+sqrt({f(i+1,j)−f(i,j+1)}²)  (5)

or

g(i,j)=abs{f(i,j)−f(i+1,j+1)}+abs{f(i+1,j)−f(i,j+1)}  (6)

When the Robert filter is used, an x-filter f_(x) and y-filter f_(y) aredefined by: $\begin{matrix}{{f_{x} = \begin{pmatrix}{- 1} & 0 & 1 \\{- 2} & 0 & 2 \\{- 1} & 0 & 1\end{pmatrix}},} & (7) \\{f_{y} = \begin{pmatrix}{- 1} & 2 & {- 1} \\0 & 0 & 0 \\1 & 2 & 1\end{pmatrix}} & (8)\end{matrix}$

and, the tilt θ of the edge is given by: $\begin{matrix}{\theta = {\tan^{- 1}( \frac{f_{y}}{f_{x}} )}} & (9)\end{matrix}$

The edge extractors perform binarization of such edge-emphasized imagesto extract edge components. The binarization is performed using anappropriate threshold value.

The time-series unification processing of depth information obtained asdescribed above will be described below with reference to FIG. 6.

FIG. 6 shows the process of generating the depth information Z 120obtained from the stereoscopic images 110 by the above-mentionedprocessing time-serially. More specifically, depth information Z^(t)(i,j) obtained at time t is input to the coordinate system converter 121,and thereafter, depth information Z^(t+δt)(i, j) obtained at time t+δtis input.

On the other hand, the posture detector 4 for detecting the movingamount, direction, and the like of the image sensing head device 1 sendsthat information to the coordinate system converter 121. The coordinatesystem converter 121 converts the depth information Z onto the unifiedcoordinate system using such position information by the processingmethod to be described below. By converting the coordinate system of thedepth information, the time-serially obtained image information can beeasily unified. As the coordinate conversion method in the coordinatesystem converter 121, for example, affine transformation is used, andidentical Euler's angles are set.

Unification of Depth Information

The processing for unifying the depth information converted onto theunified coordinate system in the depth information unificator 122 willbe described below with reference to FIGS. 8A to 10A. FIGS. 8A and 8B toFIGS. 10A and 10B are views for explaining the procedure for combiningdepth information.

FIG. 8A is a graph showing changes in depth information Z^(t)(i, j)detected at certain time t in a (Zij) space. Note that i and j representthe coordinate axes i and j perpendicular to the depth direction Z ofthe object 2.

FIG. 8B is a graph showing changes in Z′^(t+δt)(i, j) obtained byviewing depth information Z^(t+δt)(i, j) detected at time t+δt from theunified direction again in the (Zij) space.

FIG. 9A is a graph showing changes in luminance information I^(t)_(R)(i, j) in the (Zij) space. FIG. 9B is a graph showing changes inluminance information I′_(R) ^(t+δt)(i, j) viewed from the unifieddirection again.

FIG. 10A shows shifts in depth information Z^(t)(i,j) from time t totime t+δt. In FIG. 10A, (i₀, j₀) represents changes in the i and jdirections. That is, superposition of the graphs in FIGS. 8A and 8Bgives the graph in FIG. 10A.

FIG. 10B shows the state wherein Z′^(t+δt)(i, j) in FIG. 10A is shiftedby (i₀, j₀), and is superposed on Z^(t)(i, j).

As shown in FIG. 10B, upon superposing depth information, thesuperposing degree Q is calculated using, e.g., the following equation(10): $\begin{matrix}{Q =  {\sum\limits_{i = 0}^{N - 1}\sum\limits_{j = 0}^{N - 1}} \middle| {{I_{R}^{t}( {i,j} )} - {I_{R}^{{\prime \quad t} + {\delta \quad t}}( {i,j} )}} \middle| {+ {\sum\limits_{i = 0}^{N - 1}\sum\limits_{j = 0}^{N - 1}}} \middle| {{Z_{R}^{t}( {i,j} )} - {Z_{R}^{{\prime \quad t} + {\delta \quad t}}( {i,j} )}} |} & (10)\end{matrix}$

Subsequently, (i₀, j₀) that yields the minimum superposing degree Q iscalculated.

Since a bright point Z (having a luminance I) on the object at the depthZ is an identical bright point even at time t and time t+δt, the depthinformation Z and luminance information I from the identical brightpoint must assume identical values at time t and time t+δt. Hence, ifZ′^(t+δt)(i, j) coincides with Z^(t)(i, j), (i₀, j₀) minimizes theevaluation function Q.

Using the calculated (i₀, j₀), the depth information Z is shifted by(i₀, j₀) and is superposed on another depth information, as shown inFIG. 10B.

Identical Point Removal

Subsequently, identical point removal and intermediate pointinterpolation are performed. The identical point removal is performed toreduce the information volume in each depth information.

Assume that two corresponding points (x₀, y₀, z₀) and (x₁, y₁, z₁) areobtained from images at time t and time t+δt. Whether or not these twocorresponding points are identical points is determined based on therelation below. That is, if the following relation holds for aninfinitesimal constant ε₁, the two points are determined as identicalpoints, and one of these points is removed:

(x ₀ −x ₁)²+(y ₀ −y ₁)²+(z ₀ −z ₁)²<ε₁  (11)

In place of relation (11), the following relation may be used:

a(x ₀ −x ₁)² +b(y ₀ −y ₁)² +c(z ₀ −z ₁)²<ε₂  (12)

where a, b, c, and d are appropriate coefficients. For example, if a=b=1and c=2, i.e., the weighting coefficient in the z-direction is set to belarger than those in the x- and y-directions, the difference in distanceZ in the z-direction between two points can be discriminated moresensitively.

Interpolation with Intermediate Point

As the intermediate point interpolation method, a method of calculatingan intermediate point, as shown in, e.g., FIG. 11, may be used.

Note that the Zij three-dimensional space is projected onto a Z-i planein FIG. 11 for the sake of simplicity.

In FIG. 11, a point A (denoted by ◯) on the graph indicates theextracted depth information Z^(t)(i, j), and a point B (denoted by )indicates Z′^(t+δt)(i+i₀, j+j₀) obtained by shifting Z′^(t+δt)(i, j) by(i₀, j₀). Also, a point C (denoted by □) indicates the interpolatedintermediate point, i.e., new depth information Z_(new). As theinterpolation method, for example, linear interpolation, splineinterpolation, or the like is used.

Unified Coordinate System

The “unified coordinate system” used in the above-mentioned unificationprocessing will be described below with reference to FIGS. 12 and 13.

In FIG. 12, reference numeral 2 denotes an object; 3, a background planeformed by a pad; and 1800 to 1804, imaginary projection planes used forregistering depth information. Also, reference numerals 1810 to 1814denote central axes (optical axes) of the imaginary projection plane.

The “unified coordinate system” used in this embodiment means five setsof reference coordinate systems each of which is defined by (x, y, z).That is, as shown in, e.g., FIG. 12, five sets of coordinate systemsthat form the imaginary projection planes 1800 to 1804 are present.

The depth information Z^(t)(i, j) obtained by the above processing isprojected onto the individual projection planes (five planes). Uponprojection, conversions such as rotation, translation, and the like areperformed in accordance with the individual reference coordinates. Thisstate is shown in FIG. 13.

In FIG. 13, the intersections between the projection plane 1803 andstraight lines that connect the central point O on the optical axis 1813and the individual points S on the object are points P converted ontothe unified coordinate systems.

Note that FIG. 13 exemplifies the projection plane 1803, and the sameapplies to other projection planes. Also, the same applies to the nextdepth information Z^(t+δt)(i, j). In this case, each depth informationis sequentially overwritten on the previously written one. Accordingly,depth information along five reference axes is obtained for a certainobject 2. For example, one point is expressed by five points (x₀, y₀,z₀), (x₁, Y₁, z₁), (x₂, y₂, z₂), (x₃, y₃, z₃), and (x₄, y₄, z₄) on theprojection planes 1800 to 1804.

As described above, according to the first embodiment, upon unifyingdepth information, since a plurality of depth information are convertedinto a plurality of unified coordinate systems on the basis ofdisplacement information of the luminance information and distanceinformation of the object 2, the present invention can flexibly copewith dynamic image sensing which is done while moving around the object2, and can process an image to various image formats.

<Modification of First Embodiment> . . . First Modification

The first modification of the first embodiment will be described below.Note that the arrangement of the image sensing device and the imagesensing method are the same as those in the first embodiment, and adetailed description thereof will be omitted. Hence, a unificatordifferent from that in the first embodiment will be described below.

In the first modification, a correlation calculation is made using theobtained depth information alone, as shown in the following equation(13): $\begin{matrix}{Q =  {\sum\limits_{i = 0}^{N - 1}\sum\limits_{j = 0}^{N - 1}} \middle| {{Z_{R}^{t}( {i,j} )} - {Z_{R}^{{\prime \quad t} + {\delta \quad t}}( {i,j} )}} |} & (13)\end{matrix}$

More specifically, the first modification does not use any luminanceinformation I given by equation (10) in the first embodiment. Suchmethod is effective for shortening the correlation calculation timealbeit slightly.

<Modification of First Embodiment> . . . Second Modification

The second modification will be described below. Note that thearrangement of the image sensing device and the image sensing method arethe same as those in the first embodiment, and a detailed descriptionthereof will be omitted. Hence, a unificator different from that in thefirst embodiment will be described below.

In the second modification, as the method of interpolation, weighting isperformed using luminance level given by equation (14) below.

For example, equation (14) is used as a weighting coefficient t:$\begin{matrix}{t = {{\frac{1}{2} \cdot {\tanh ( {{I_{R}^{t}( {i,j} )} - {I_{R}^{{\prime \quad t} + {\delta \quad t}}( {i,j} )}} )}} + \frac{1}{2}}} & (14)\end{matrix}$

Subsequently, in order to obtain new depth information Z byinterpolation, weighting is performed as follows as a kind of linearinterpolation:

Z _(new) =t·Z ₁+(1−t)·Z ₂  (15)

<Advantages of First Embodiment>

As described above, according to the first embodiment and itsmodifications, upon unifying depth information, since a plurality ofdepth information are converted into a plurality of unified coordinatesystems on the basis of displacement information of the luminanceinformation and distance information of the object 2, the presentinvention can flexibly cope with dynamic image sensing which is donewhile moving around a certain object, and can process an image tovarious image formats.

<Second Embodiment>

In the first embodiment mentioned above, depth information is convertedonto the unified coordinate systems on the basis of the displacements ofthe luminance information and distance information of the object. Athree-dimensional information extraction apparatus of the secondembodiment has as its object to improve reliability in three-dimensionalinformation processing. Accordingly, the system of the second embodimenthas many common elements to those in the system of the first embodiment.That is, the second embodiment directly uses, as its hardwarearrangement, the elements of the first embodiment shown in FIGS. 2 to 4.

That is, the system of the second embodiment has substantially the sameimage processor 220 as in the first embodiment, except that the imageprocessor 220 has a distance information distribution processor 116′ anda reliability determining unit 130, as shown in FIG. 14. Note that“distance information” is information having the same concept as “depthinformation”. Hence, the arrangement and operation of the distanceinformation distribution processor 116′ of the second embodiment will beunderstood by reference to those associated with the depth informationdistribution processor 116 of the first embodiment.

Elements different from those in the first embodiment in FIG. 14 will bedescribed below. The distance information distribution processor 116′calculates the distance information distribution using the principle oftrigonometric measurements on the basis of the relationship amongcorresponding points. The reliability determining unit 130 determinesreliability.

Note that the reliability determining unit 130 determines thereliability level of the calculated distance information on the basis ofthe output from the occlusion determining unit 115, the processingresult of the distance information distribution processor 116′, and theimage sensing parameters and position information from the correctiondata calculation unit 118, and adds reliability informationcorresponding to the reliability level to the calculated distanceinformation.

FIG. 15 is a block diagram showing the image processor 220 in moredetail, and mainly shows the arrangement portion associated withunification of distance information of the object 2 in the imageprocessor 220.

In order to perform unification processing of the distance informationof the object 2, as shown in FIG. 15, the image processor 220 comprisesa coordinate system converter 121 for converting distance information(Z^(t)(i, j)) from a pair of stereoscopic images 110 calculated by theindividual units onto a unified coordinate system, a distanceinformation unificator 122 for unifying the distance informationconverted onto the unified coordinate system, and a display unit 124 fordisplaying the unified distance information. The image processor 220also comprises a unit for outputting occlusion region information to theunificator 122 and the display unit 124, and a unit for detecting themoving amount and direction of the image sensing head device 1, and thelike.

Note that “unification” is to set identical points so as to convert eachdistance information 120 into one viewed from a single coordinate systemon the basis of displacement information between two distanceinformation data 120 of the object 2 obtained from at least twoarbitrary positions. Also, “unification” implies interpolationprocessing of coordinates (to be described later), determining thereliability of coordinates of a point or area on the basis of areliability coefficient obtained from reliability information of thedistance information, and the like.

Reliability Determination

The processing sequence of the image head device 1 of thethree-dimensional information processing apparatus according to thesecond embodiment will be described below with reference to the flowchart in FIG. 16.

When the power supply is turned on (step S1) and image signals areinput, the controller 210 integrates the image signals obtained from theimage separators 105R and 105L using the image processing section 920 tocalculate the luminance level of the principal object 2 (step S2). If itis determined that the calculated luminance level is insufficient forthree-dimensional shape extraction, the controller 210 turns on theillumination unit 200 (step S3). At this time, the illuminationintensity level may be varied in correspondence with the calculatedluminance level.

Subsequently, in-focus points are adjusted using the individual imagesignals set at appropriate luminance level (step S5). At this time, thelenses 100R and 100L are moved to form focal points on both theprincipal object 2 and the background plane 3, and the iris diaphragms108R and 108L are adjusted. At that time, when the luminance levelchanges by a given amount or more, the intensity of the illuminationunit 200 is changed to compensate for that change in luminance level.Alternatively, an AGC (auto-gain control) circuit may be assembled toattain electrical level correction. The focusing state is detected bythe focusing state detector 270. As a detection method for this purpose,a method of detecting the sharpness of an edge, or the defocus amountmay be used.

After the in-focus points are adjusted, zoom ratio adjustment is done(step S6).

FIG. 17 shows the outline of zoom ratio adjustment in the system of thesecond embodiment.

In the state wherein the principal object 2 roughly falls within thefocal depth, images obtained from the individual image sensing systems100R and 100L are held in the memory 910 of the controller 210, and theimage processing section 920 detects the overlapping region. In thiscase, correlation calculation processing, template matching processing,or the like is used as the detection method.

As shown in FIG. 17, an overlapping region 500 is detected in theinitial state, and thereafter, the controller 210 sets the zoom ratio ina direction to increase the area of the region in the frames of the twoimage sensing systems and outputs control signals to the zoomcontrollers 106R and 106L.

FIG. 18 shows changes in overlapping region in the frame by a series ofzoom ratio adjustment processes. In FIG. 18, the image processingsection 920 of the controller 210 calculates a focal length f at whichthe overlapping region has a peak area P in FIG. 18, and control signalsare supplied to the zoom controllers 106R and 106L.

When the focal length f changes by the above-mentioned operation, andconsequently, the focal depth range changes by a given amount or more,control signals are supplied to the iris diaphragm controllers 108R and108L in accordance with step S200 (steps S1 to S5) of readjustingparameters in FIG. 16.

After step S100 (including a series of adjustment steps S1 to S7),readjustment of parameters and adjustment of an R-L difference in stepS200 are performed. In the adjustment of the R-L difference, the R-Ldifference discriminator 260 detects the exposure amounts, in-focuspoints, and zoom ratios from image signals. Based on the detectedsignals, the controller 210 supplies control signals to the zoomcontrollers 106R and 106L, focus controllers 107R and 107L, and irisdiaphragm controllers 108R and 108L.

Note that various image sensing parameters upon image sensing include,e.g., the focal length, which can be set by the method (equations (1) to(3)) described in the first embodiment.

After the image sensing parameters are adjusted in steps S100 and S200,the controller 210 supplies a signal to the display unit 240 to informthe user of the end of parameter setting (step S8). Note that thedisplay unit 240 may comprise a display such as a CRT, an LCD, or thelike, or may perform simplified indication using an LED or the like.Also, a sound may be produced as well as visual information.

Upon completion of parameter setting, the user presses the releasebutton at appropriate intervals while moving the image sensing headdevice 1 to input images (steps S9 to S11). In this case, the movingspeed, position, and the like of the image sensing head device 1 arealso detected (steps S12 to S14).

The method of extracting distance information from stereoscopic images110 by the image processor 220 is substantially the same as extractionof depth information in the first embodiment.

The corresponding point extraction processing in the second embodimentuses the template matching method as in the first embodiment.

In this manner, edge-emphasized images are subjected to binarization toextract edge components. Note that the binarization is made using anappropriate threshold value.

In the next image extraction processing step, the occlusion region isdetermined by the occlusion region determining unit 115 on the basis ofthe calculated corresponding points and an index (e.g., a residual)indicating the degree of correlation used in the process of calculatingthe corresponding points.

This processing is to add reliability to the results of thecorresponding point processing, although the corresponding pointprocessing yields tentative results. Reliability information is addedusing a correlation coefficient or residual as an index indicating thedegree of correlation. If the residual is very large, or if thecorrelation coefficient is low, it is determined that the reliability ofthe correspondence is low. The low-reliability portion is processed asan occlusion region or a region without any correspondence.

More specifically, as shown in FIG. 19, if the residual per pixel fallswithin the range from 0 to 2, the reliability coefficient is 3; if theresidual per pixel falls within the range from 2 to 4, the reliabilitycoefficient is 2; and if the residual per pixel is 4 or more, thereliability coefficient is 0. When the reliability coefficient is 0, thecorresponding pixel is deleted.

Via the above-mentioned processing steps, the distance information ofthe object is calculated using the calculated correspondence and theprinciple of trigonometric measurements. The trigonometric measurementsare attained as described above using equation (1).

Subsequently, since the position and image sensing direction of theimage sensing head device 1 upon image sensing can be detected from theoutput from the correction data calculation unit 118, the reliabilitydetermining unit 130 determines reliability of the distance informationbased on the calculation result from the unit 118. The calculateddistance information is expressed as a point group on the coordinatesystem determined by the data of the background plane 3. At this time,when a region between the edge portions as the outputs from the edgeextractors 111 undergoes an abrupt change in distance, the correspondingdistance information is deleted. This is because when the distancechanges abruptly, it is very likely that such portion is recognized asan edge portion.

The distances from the image sensing plane to the individual points arecalculated, and the tilt of an area defined by adjacent three pointswith respect to the image sensing plane is calculated. The tilts ofneighboring areas are checked, and if the difference between their tiltsis negligibly small, the area is extended until all the areas having thesame tilt are combined. Thereafter, reliability information is added toeach area. In this case, the area is not extended to an occlusionportion or a portion from which the distance information is deleted. Atthis time, information as a point group may be held, but is preferablydeleted to compress the information volume.

The reliability information is determined and added in correspondencewith the angle with respect to the image sensing plane and the residual,as shown in FIG. 20.

In the case of FIG. 20, when the angle with respect to the image sensingplane falls within the range from 0° to 30° and the residual fallswithin the range from 0 to 2, the reliability coefficient is 3 whichindicates the highest reliability. On the other hand, when the anglewith respect to the image sensing plane falls within the range from 80°to 90° and the residual falls within the range from 2 to 4, thereliability coefficient is 0 which indicates the lowest reliability. Thedata of the area with the reliability coefficient=0 may be deleted asunreliable data.

In this manner, reliability data is added to each area as 2-bitinformation having different reliability coefficients 3, 2, 1, and 0 incorrespondence with the angle of the area. Thereafter, three-dimensionalshape information is recorded in the recorder 250 after it is convertedinto an appropriate format.

As described above, since image sensing is performed at a plurality ofpositions A₀ to A_(n), all the sensed images do not always include thebackground plane 3 with a size large enough to precisely obtaincharacteristic points. For this reason, reliability information is addedin correspondence with the ratio of the background plane 3 to the imagesensing region. The background plane 3 can be detected by the imageseparator 105. For example, when the ratio falls within the range from100 to 30%, the reliability coefficient is 3; when the ratio fallswithin the range from 30 to 15%, the reliability coefficient is 2; andwhen the ratio is 15% or less, the reliability coefficient is 1. Whenthe image sensing region includes almost no pad image of the backgroundplane 3, since the reference coordinate system cannot be determined,distance information must be unified using, e.g., texture information.Accordingly, in such case, a low reliability coefficient is set sincereliability may be impaired otherwise. The reliability coefficientdetermined based on the angle with respect to the image sensing planeand the residual is changed in correspondence with that reliabilitycoefficient, and the changed coefficient is added to the distanceinformation as a new reliability coefficient.

A distance image obtained from the right and left images can bedisplayed on the monitor 8. The image displayed at that time can beselected from a natural image, line image, and polygon image, asdescribed above, and in any one of the display patterns, reliabilityinformation can be displayed at the same time. A natural image isdisplayed while the luminance of each region is changed incorrespondence with the reliability coefficient. On the other hand, aline image is displayed while changing the thickness or type of lines(e.g., a solid line, broken line, chain line, and the like). Also, apolygon image is displayed by changing the colors of polygons. In thismanner, the reliability information can be displayed at the same time.

The time-series unification processing of the distance informationobtained as described above will be described below with reference toFIG. 15.

Distance information 120 is time-serially generated based on theobtained stereoscopic images 110, while the unit for detecting themoving amount, direction, and the like of the image sensing head device1 sends that information. The coordinate system converter 121 convertsthe distance information onto a unified coordinate system using suchinformation by the processing method (to be described later). Convertingthe distance information allows easy unification of information obtainedtime-serially.

Subsequently, a plurality of distance information converted onto theunified coordinate system are unified.

Upon unification, the reliability information is used. For example,assuming that two distance information data are obtained, and they havedifferent reliability coefficients in their overlapping portion, theinformation with a higher reliability is selected. Or information may beunified while being weighted in correspondence with their reliabilitycoefficients. When three or more overlapping region data are present,unification is similarly done in correspondence with the reliabilitycoefficients. Thereafter, the reliability coefficient is added to theunified distance information. Since data with higher reliability isselected upon unification, the reliability of the unified distanceinformation can be improved.

As shown in FIG. 15, the unificator 122 of the second embodimentexecutes processing for removing identical points and intermediate pointcorrection processing as in the first embodiment.

In the system of the second embodiment, since the “unified coordinatesystem” used in the above-mentioned unification processing is explainedby FIGS. 12 and 13 as in the first embodiment, a detailed descriptionthereof will be omitted.

The unified distance information can be displayed on the monitor 8. Thethree-dimensional shape of the object viewed from an arbitrary viewpoint can be observed by operating the operation unit 11. At this time,the reliability information can be displayed at the same time as in thecase wherein the distance information obtained from the right and leftimages is displayed. With this display, since a low-reliability regioncan be determined at a glance, the user can recognize the region to beadditionally sensed, and can perform additional image sensing.

<Modification of Second Embodiment>Third Modification

The third modification of the second embodiment will be explained below.

FIG. 21 shows the outline of the third modification.

Referring to FIG. 21, reference numeral 2101 denotes a principal object;2100, a three-dimensional shape extractor of the three-dimensionalinformation processing apparatus; 100, an image sensing lens; and 200,an illumination unit. Also, reference numeral 2102 denotes a calibrationpad. The three-dimensional shape extractor detects the posture based onthe image of this pad. Note that letters A, B, C, and D on the pad 2102serve as markers used for detecting the posture of the extractor 2100.The posture of the camera can be calculated based on the directions ofthese markers, distortions of marker images, and the like.

FIG. 22 is a block diagram showing the three-dimensional shape extractor2100 according to the third modification in detail. Note that thecomponents denoted by the same reference numerals in FIG. 22 except forsymbols R and L have the same functions and operations as those in thesecond embodiment, and a detailed description thereof will be omitted.As shown in FIG. 22, the three-dimensional shape extractor 2100 hassubstantially the same functions and operations as those in the secondembodiment, except that it has a single-lens arrangement.

The operation in the third modification will be explained below.

Since the apparatus of the third modification attains posture detectionin combination with the pad 2102, the image of the pad 2102 must beobtained within an appropriate range upon image sensing. The imageseparator 105 performs calculations or template matching between thepre-stored feature portions (the four corners A, B, C, and D in FIG. 21)and an image which is being currently sensed, and outputs the detectionsignal to the system controller 210. The system controller 210 sets thefocal length so that the image of the pad 2102 falls within anappropriate range in the field of view. At the same time, the systemcontroller 210 holds the focal length information in its memory 910.

With this processing, since the image of the entire pad is kept withinthe field of view, the posture can always be detected based on theshapes of the markers. Also, since the image of the entire pad alwaysfalls within the field of view, reliability can be improved in thecorresponding point extraction processing. Since the principal object2101 is present in front of the pad, if the calculated distanceinformation exceeds the pad, that calculation result can be deleted.Also, since the pad region can be determined, the search region forextracting corresponding points can be limited, and consequently, alarge template size can be used to improve precision for correspondingpoint extraction.

FIG. 23 is a flow chart showing the operation of the three-dimensionalinformation processing apparatus according to the third modification.

As shown in the flow chart in FIG. 23, when the power supply is turnedon, and various parameters of the optical system such as an exposurecondition, in-focus point adjustment, and the like are set (steps S21 toS25), an LED of the display unit 240 is turned on (step S26) to informthe user of the input ready state. In response to this indication, theuser starts input (step S27) and presses the release button 230 atappropriate intervals while moving the extractor 2100 so as to inputimages (step S28). At this time, the system controller 210 sets thefocal length on the basis of information from the image separator 105 sothat the characteristic portions of the pad 2102 including the principalobject fall within an appropriate range in the field of view. At thesame time, the system controller 210 stores image sensing parameterinformation including the focal lengths at the individual image sensingpositions in the memory 910. The posture detector 4 detects the posturebased on the states of the characteristic portions (step S29).

The image processor 220 reads out a plurality of image signals held inimage memories 73 and 75, and converts and corrects images into thosewith an identical focal length on the basis of the image sensingparameter information held in the memory 910 of the system controller.Furthermore, the image processor 220 extracts the object shape using thecorrected image signals and the posture signal detected by the posturedetector 4.

Thereafter, reliability information is added to the obtainedthree-dimensional shape information. In the third modification, thereliability information is determined and added in correspondence withthe angle with respect to the image sensing plane and the distance fromthe image sensing plane, as shown in FIG. 24.

In the case of FIG. 24, when the angle with respect to the image sensingplane falls within the range from 0° to 30° and the object distancefalls within the range from 10 cm to 30 cm, the reliability coefficientis 3, and this value indicates the highest reliability. On the otherhand, when the angle with respect to the image sensing plane fallswithin the range from 80° to 90° and the object distance is 60 cm, thereliability coefficient is 0, and this value indicates the lowestreliability. The data of an area with the reliability coefficient=0 maybe deleted. In this manner, reliability data is added as 2-bitinformation to each area.

The three-dimensional shape information added with the reliabilityinformation is supplied to the recorder 250. The recorder 250 convertsthe input signal into an appropriate format, and records the convertedsignal.

<Advantages of Second Embodiment>

As described in detail above, according to the second embodiment, sincethe reliability of the extracted three-dimensional shape information isdetermined on the basis of the angle of the object with respect to theimage sensing plane, the object distance, and the image correspondencethat can be discriminated from the residual or correlation, thereliability of the obtained three-dimensional shape information can beimproved. When the three-dimensional shape information is processed anddisplayed in correspondence with the reliability, the user can bevisually informed of the reliability.

In the second embodiment and third modification, the reliability isdetermined using the residual or correlation upon extractingcorresponding points, the angle of the object with respect to the imagesensing plane and object distance, the ratio of the pad image withrespect to the image sensing region, and the position information of thepad. In addition to them, the reliability of the obtainedthree-dimensional shape can also be determined using light emitted by alight source and reflected by the object and the angle of the pad withrespect to the image sensing plane.

A case using light emitted by a light source and reflected by the objectwill be explained below.

Light reflected by the object can be discriminated to some extent on thebasis of the luminance information of image signals. This is becausewhen the reflectance of the object is high, the luminance becomes veryhigh over a certain range at the position where the reflected lightenters the lens. The portion with the high luminance is removed as thatobtained by reflection. More specifically, threshold values aredetermined in correspondence with the respective luminance levels, andthe reliability coefficients of 0 to 3 are determined in accordance withthe threshold values.

A case using the angle of the pad with respect to the image sensingplane will be explained below.

In this case, the reliability coefficients are added in correspondencewith the angle of the pad like in a case wherein the reliabilitycoefficients are set in correspondence with the angle of the object withrespect to the image sensing plane. This utilizes the fact that if thereliability of the reference coordinate system is low, thethree-dimensional shape on the reference coordinate system also has lowreliability since the reference coordinate system is obtained from thepad. For example, when the angle of the object falls within the rangefrom b 0° to 60°, the reliability coefficient is 3; when the angle ofthe pad falls within the range from 60° to 75°, the reliabilitycoefficient is 2; when the angle of the pad falls within the range from75° to 85°, the reliability coefficient is 1; and when the angle of thepad falls within the range from 85° to 90°, the reliability coefficientis 0. The reason why the pad angle detection is set to have higherreliability than the object angle detection is that the angle can beprecisely calculated from a plurality of data by, e.g., the method ofleast squares since the pad is recognized as a plane in advance.

In the above description, the reliability coefficient is 2-bitinformation, but the number of bits may be increased as needed.

As described above, according to the second embodiment, since thereliability of the extracted three-dimensional shape information isdetermined on the basis of the angle of the object with respect to theimage sensing plane, the object distance, and the image correspondencethat can be discriminated from the residual or correlation, thereliability of the obtained three-dimensional shape information can beimproved. When the three-dimensional shape information is processed anddisplayed in correspondence with the reliability, the user can bevisually informed of the reliability.

<Third Embodiment>

The third embodiment aims at improving the image sensing timing.

FIG. 25 is a diagram showing the arrangement and use state of anautomatic image sensing apparatus 1100 as an image sensing apparatusaccording to the third embodiment of the present invention. In FIG. 25,the same reference numerals denote the same parts as in the previouslydescribed prior art shown in FIG. 1. The differences in FIG. 25 fromFIG. 1 are that a posture sensor 1128, a process controller 1129, and anobject recognition circuit 1130 are added to the arrangement shown inFIG. 1. In FIG. 25, reference numerals 1142 and 1143 denote signallines.

In the automatic image sensing apparatus 1100 of the present invention,a plurality of means can be used as image sensing condition detectionmeans and, for example, the posture sensor 1128, an image sensingparameter detection circuit 1123, the object recognition circuit 1130,and a corresponding point extraction circuit 1122 in FIG. 25 correspondto such means.

The operation when these constituting elements are used will beexplained below.

The operation in the simultaneous processing mode will be exemplifiedbelow.

In the automatic image sensing apparatus 1100, the posture sensor 1128always detects the rotation angle and moving amount of the apparatus1100, and the process controller 1129 process-controls to input imagesignals to storage circuits 1120 and 1121 every time the automatic imagesensing apparatus 1100 changes to a predetermined position and by apredetermined angle. When the posture sensor 1128 detects that theapparatus 1100 has completed one revolution around an object 1101, theprocess controller 1129 reads out images from the image signal storagecircuits 1120 and 1121, and starts simultaneous processing of thecorresponding point extraction circuit 1122, the image sensing parameterdetection circuit 1123, and a three-dimensional information unifyingcircuit 1125.

FIG. 26 shows the arrangement of the posture sensor 1125 in detail. Asshown in FIG. 26, three small vibration gyros 1201, 1202, and 1203 arearranged so that their axes extend in directions perpendicular to eachother, and independently detect the rotation angular velocities (pitch,yaw, and roll) of the automatic image sensing apparatus 1100.Integrators 1203, 1204, and 1205 respectively integrate the detectedvalues, and convert them into rotation angles of the automatic imagesensing apparatus 1100. When the photographer performs image sensing sothat an object 1101 always falls within the frame, the rotation anglesof the automatic image sensing apparatus 1100 itself substantially matchinformation indicating the degree of revolution of the automatic imagesensing apparatus 1100 around the object 1101. Based on suchinformation, when the pitch or yaw angle has changed by a predeterminedangle, the process controller 1129 controls to store images. Althoughchanges in the roll direction are not directly used in process control,if the automatic image sensing apparatus 1100 rolls considerably andboth pitch information and yaw information are mixed and output, theroll information is used for accurately separating these outputs. Themerits of the arrangement using the angular velocity sensors are a verycompact arrangement, high sensor sensitivity, and very high precisionowing to only one integration.

The posture sensor 1128 may be constituted by acceleration sensors todetect accelerations.

FIG. 27 shows the layout of acceleration sensors 1301, 1302, 1303, 1304,1305, and 1306 that make up the posture sensor 1128. In general, sincean acceleration sensor detects linear vibrations, a pair of sensors arearranged parallel to each other. Reference numerals 1310 to 1315respectively denote integrators each for performing integration twice.Each integrator integrates the corresponding acceleration sensor outputtwice to calculate the position moving amount. When the integral outputsfrom a channel consisting of a pair of acceleration sensors are added toeach other, translation components (X, Y, Z) in the attachment directionof the pair of acceleration sensors can be obtained; when the outputsare subjected to subtraction, rotation components (α, β, γ) can beobtained. To attain such calculations, adders 1320, 1321, and 1322, andsubtractors 1330, 1331, and 1332 are arranged.

The process controller 1129 checks the moving amount of the automaticimage sensing apparatus 1100 relative to the object 1101 to control theimage input timings to the image signal storage circuits 1120 and 1121.Although this detection method requires a complicated sensorarrangement, since all the degrees of freedom (horizontal X, vertical Y,back-and-forth Z, pitch α, yaw β, and roll γ) of the automatic imagesensing apparatus 1100 can be detected at the same time, changes in viewpoint with respect to the object 1101 can be accurately detected.

Furthermore, as for some methods for detecting the relative positionrelationship between two objects in a non-contact manner, “Survey ofhelmet tracking technologies” SIP Vol. 1456 Large-Screen-Projection,Avionics, and Helmet-Mounted Displays (1991) p. 86 (to be referred to asa reference hereinafter) has descriptions about the principles,characteristics, and the like of the individual methods.

Such principles can be applied to the posture sensor 1128 of theautomatic image sensing apparatus 1100. This reference describes theprinciple of analyzing relative position on the basis of bright pointimages sensed by a camera. When such technique is applied to theautomatic image sensing apparatus 1100, the image sensing parameterdetection circuit 1123 is controlled to operate all the time using thesignal lines 1142 and 1143 in FIG. 25 without going through the imagesignal storage circuits 1120 and 1121. The image sensing parameterdetection circuit 1123 analyzes an image of a known bright pointpattern, and detects the moving amount and posture of the automaticimage sensing apparatus 1100.

FIG. 28 shows an example of the image storage timings of the automaticimage sensing apparatus 1100.

In FIG. 28, reference numeral 1400 denotes a path formed when thephotographer manually holds and moves the automatic image sensingapparatus 1100 around the object 1101. Reference numeral 1401 denotes animage sensing start position, which corresponds to the storage timing ofthe first image.

Also, reference numerals 1402, 1403, 1404, 1405, . . . , 1409 denote thedetection timings of changes, by a predetermined amount, in X- orY-direction or in rotation angle α or β under the assumption that theimage sensing system points in the direction of the object 1101, andimages are stored at the timings of these positions 1402, 1403, 1404,1405, . . . , 1409.

At the timing of the position 1409 corresponding to the end of onerevolution, the coordinate X and the rotation angle β assume valuesequal to those at the position 1401, but other values (Y, Z, α, γ) donot always match those at the position 1401. However, in the automaticimage sensing apparatus 1100, the start and end points need not alwaysstrictly match, and when Y, Z, and α are smaller than predeterminedvalues, image input is terminated when X and β match those at the startpoint.

The automatic image sensing apparatus 1100 need always be moved in aplane (e.g., the path 1400 in FIG. 28) parallel to the ground to performimage sensing. For example, an image sensing method of moving theapparatus 1100 above the object 1101 may be used.

In FIG. 28, reference numeral 1410 denotes a path when the photographermanually holds and moves the automatic image sensing apparatus 1100above the object 1101 to perform image sensing. Reference numerals 1411,1412, 1413, . . . , 1419 denote storage timing positions. In this imagesensing mode, the values Y and α are detected in place of X and β toperform image input control, and when a has changed 180°, the imageinput is stopped.

FIGS. 29A to 29C show an example of input images obtained when the imageinput is made at the timings of the positions 1401 to 1405. As can beseen from FIGS. 29A to 29C, time-serial images obtained by viewing theobject 1101 in turn from slightly different view points are obtained.

FIGS. 30A to 30C show an example of the image input timings differentfrom those in FIGS. 29A to 29C. In an image sensing mode of thisexample, an image sensing unit set with a large image sensingmagnification is used, so that the object 1101 falls outside the frame.In this mode, the automatic image sensing apparatus 1100 is moved inroughly the X-direction to perform image sensing. In such image sensingmode, when the overlapping region with the previously sensed image ineach frame reaches a predetermined area, i.e., at the timing at whicheach hatched portion in FIGS. 29A to 29C reaches the predetermined area,the sensed images are stored in the image signal storage circuits 1120and 1121. In this mode, since a large image sensing magnification isset, the image and shape of the object 1101 can be analyzed in detail,and continuous images can be stably input under the control of theprocess controller 1129.

In the above description, signal storage and process control operationsare attained based on the position and angle of the automatic imagesensing apparatus 1100. Also, the storage and process control operationsmay be attained by analyzing the image itself of the object 1101, aswill be described below.

For example, the object recognition circuit 1130 shown in FIG. 25 isused. The object recognition circuit 1130 detects changes in objectimage from changes over time in image signal. For example, thedifference from a past image is detected, and when the differencereaches a predetermined value, image signals are input. Since thismethod does not directly detect the movement of the automatic imagesensing apparatus 1100, the processing timing precision is low, butsince the processing is simple and no extra sensor is required, theentire automatic image sensing apparatus 1100 can be rendered compact.

Furthermore, the corresponding point extraction circuit 1122 in FIG. 25may operate all the time, and distance image data output from thiscorresponding point extraction circuit 1122 may be analyzed to attainprocess control. When the automatic image sensing apparatus 1100 hasmoved by a predetermined amount, the detected distance image changesaccordingly. When time changes in distance image reach a predeterminedamount, image input can be performed. In this method, when the object1101 has a large uneven portion, a large signal is output even whenchanges in position of the image sensing system are small. For thisreason, image sensing is controlled for such uneven portion at shortintervals, otherwise, image sensing is controlled at long intervals. Ingeneral, since the shape of such uneven portion is to be analyzed indetail, images can be input more efficiently according to this method.

Similarly, a method of using an error signal output from thecorresponding point extraction circuit 1122 in FIG. 25 is alsoavailable. Note that the error signal is information which indicates apixel position where corresponding points cannot be normally detectedupon detecting corresponding points in image signals obtained from theright and left image sensing units in units of pixels. Such phenomenonoccurs when so-called occlusion has occurred, i.e., a portion that canbe viewed from one image sensing unit cannot be viewed from the otherimage sensing unit, when the illumination conditions of the right andleft image sensing units are considerably different from each other,e.g., when directly reflected light from the illumination unit entersonly one image sensing unit, when the surface of the object 1101 is flatand has no texture, and corresponding points cannot be detected, and soon. However, such image sensing conditions may allow corresponding pointextraction and may not cause any errors if the view point of the imagesensing apparatus is changed.

In the automatic image sensing apparatus 1100, process control isperformed at a timing at which such error output of the correspondingpoint extraction circuit 1122 time-serially changes, so as to inputimages. In this method, as the characteristic information of the object1101, which cannot be accurately detected at a certain timing due to,e.g., occlusion, can be compensated for by an image at another timing,the three-dimensional shape of even an object with a large unevennesscan be efficiently extracted.

The processing flow controlled by the process controller 1129 will bedescribed below.

In the above description, the image input timings to the image signalstorage circuits 1120 and 1121 in the simultaneous processing mode havebeen explained. The automatic image sensing apparatus 1100 also has asequential processing mode for performing shape extraction processingwhile sensing images of the object 1101. In this case as well, when anunnecessarily large number of images are to be processed, thecalculation volumes of the corresponding point extraction circuit 1122,the image sensing parameter detection circuit 1123, and thethree-dimensional information unifying circuit 1125 increase, and outputdata from the signal lines 1140 and 1141 become large. As a consequence,the buffer circuits 1126 and 1127 require a large storage capacity.

In view of this problem, using the output from the above-mentionedposture sensor 1128 and information of the sensed images, the processcontroller 1129 controls the processing start timings of thecorresponding point extraction circuit 1122, the image sensing parameterdetection circuit 1123, and the three-dimensional information unifyingcircuit 1125. More specifically, when the automatic image sensingapparatus 1100 is moved along the path 1400 in FIG. 28, the imagessensed at the position 1401 are processed by the corresponding pointextraction circuit 1122 and the image sensing parameter detectioncircuit 1123 to extract a distance image. Subsequently, even when theprocessing has ended before the apparatus 1100 is moved to the position1402, images acquired during the movement are not processed, and thecorresponding point extraction circuit 1122 and the image sensingparameter detection circuit 1123 are stopped. During this interval,image signals obtained from image sensing elements 1114 and 1115 arediscarded or shutters 1112 and 1113 are closed to stop scanning of theimage sensing elements 1114 and 1115. With this control, the consumptionpower of the image processing circuits and the peripheral circuits ofthe image sensing elements 1114 and 1115, which consume large electricpower, can be reduced. Subsequently, when the automatic image sensingapparatus 1100 is located at the position 1402 in FIG. 28, theprocessing of the corresponding point extraction circuit 1122, the imagesensing parameter detection circuit 1123, and the three-dimensionalinformation unifying circuit 1125 is started in synchronism with thebeginning of vertical scanning of the image sensing elements 1114 and1115.

When the moving speed of the automatic image sensing apparatus 1100 ishigh and processing cannot be done within a given period, images thatcannot be processed are sequentially stored in the image signal storagecircuits 1120 and 1121. The process controller 1129 transfers the nextimages from the image signal storage circuits 1120 and 1121 by detectingthe end of processing in the corresponding point extraction circuit 1122and the image sensing parameter detection circuit 1123.

The above-mentioned embodiment has exemplified a case using two imagesensing units. The image input timing control of the present inventioncan be similarly applied to an apparatus which analyzes thethree-dimensional shape using a single image sensing unit.

As described above, according to the image sensing apparatus of thethird embodiment, since the image input control and processing startcontrol are done in correspondence with the position/angularrelationship between the object 1101 and the image sensing apparatus1100 and changes in object image, the capacities of the image signalstorage circuits 1120 and 1121 and the buffer circuits 1126 and 1127 canbe minimized, and complicated image processes can be attained within aminimum required time.

<Modification of Third Embodiment> . . . Fourth Modification

The fourth modification of the third embodiment of the present inventionwill be described with reference to FIGS. 31 and 32.

The fourth modification is applied to a system in which a plurality ofimage information sensed by moving around an object are directly stored,and the input image is selected and displayed as it is in place of a CGimage. The following description will exemplify a case wherein two imagesensing units are used to easily obtain sense of reality, and astereoscopic image is displayed on a stereoscopic display. However, theimage input timing control of the present invention can also be appliedto a system using a single image sensing unit.

FIG. 31 is a diagram showing the arrangement and operation principleupon acquisition of images of an image sensing apparatus 1700 accordingto the fourth modification, and the same reference numerals in FIG. 31denote the same parts as in FIG. 25 of the third embodiment describedabove. The differences in FIG. 31 from FIG. 25 are that circuitsassociated with stereoscopic image analysis such as the correspondingpoint extraction circuit 1122, image sensing parameter detection circuit1123, ROM 1124, three-dimensional information unifying circuit 1125,buffer circuits 1126 and 1127, and the like are omitted from thearrangement shown in FIG. 25, and an image sensing condition storagecircuit 1702 is added to the arrangement in FIG. 25.

In the fourth embodiment, the image signal storage circuits 1120 and1121 are housed in a storage unit 1701, which is detachable from theimage sensing apparatus 1700, together with the image sensing conditionstorage circuit 1702, and upon completion of image sensing, the storageunit 1701 can be detached and carried.

In the image sensing apparatus 1700 according to the fourthmodification, the image sensing positions and angles detected by theposture sensor 1128 are stored in the image sensing condition storagecircuit 1702 simultaneously with the sensed images.

Since other arrangements and operations in the image sensing apparatus1700 according to the fourth modification are the same as those in theimage sensing apparatus 1100 according to the third embodiment, adetailed description thereof will be omitted.

FIG. 32 shows the arrangement of an image display means for displayingan image sensed by the image sensing apparatus 1700.

In FIG. 32, reference numeral 1801 denotes an image reproduction unit;1802, a stereoscopic display; 1803, a three-dimensional mouse; and 1804,a coordinate comparison circuit. The storage unit 1701 stores imagesaround the object 1101, and their image sensing directions andpositions. When the operator designates the observation direction of theobject 1101 using the three-dimensional mouse 1803, the coordinatecomparison circuit 1804 checks if an image in the designated observationdirection is stored in the image sensing condition storage circuit 1702.If an image in the designated observation direction is stored, imagedata are read out from the image signal storage circuits 1120 and 1121and are displayed on the stereoscopic display 1803. On the other hand,if an image in the designated observation direction is not stored, animage closest to the designated image is retrieved, and is displayed onthe stereoscopic display 1803.

Since such image sensing/display system does not calculate astereoscopic image as numerical value information but selects anddisplays an image in the view point direction desired by the operator,an object image which is discrete but is viewed virtually from anarbitrary direction can be instantaneously displayed. Hence, theoperator can feel as if an actual object were present there.

As described above, according to the image sensing apparatus 1700 of thefourth modification, even when the operator does not move the apparatusat a constant speed around the object, images can be properly input atappropriate positions. Accordingly, a display image relatively close tothat in the direction designated by the observer can always bepresented.

As many apparently widely different embodiments of the present inventioncan be made without departing from the spirit and scope thereof, it isto be understood that the invention is not limited to the specificembodiments thereof except as defined in the appended claims.

What is claimed is:
 1. An image sensing method comprising: the imagesensing step of sensing images of an object; the storage step of storingimage information of the object; the image sensing condition detectionstep of detecting a relative relationship between the object and animage sensing apparatus main body; and the control step of controlling astorage operation of the image information, wherein the control stepincludes the step of controlling the storage operation in the storagestep in accordance with a detection result of the image sensingcondition detection step.
 2. The method according to claim 1, whereinthe control step includes the step of controlling to store informationassociated with the relative relationship between the object and theimage sensing apparatus main body together with sensed images sensed inthe image sensing step in the storage step.
 3. The method according toclaim 1, wherein the image sensing condition detection step includes thestep of detecting the relative relationship using a sensor for detectingan angle and translation movement of the image sensing apparatus mainbody.
 4. The method according to claim 1, wherein the image sensingcondition detection step includes the step of analyzing an object imageand images around the object sensed by the image sensing apparatus mainbody, and detecting an angle and translation movement of the imagesensing apparatus main body on the basis of changes in state of sensedimages sensed in the image sensing step.
 5. The method according toclaim 1, wherein the image sensing condition detection step includes thestep of analyzing an object image and images around the object sensed bythe image sensing apparatus main body, and detecting changes in relativeposition relationship between the object and the image sensing apparatusmain body on the basis of an error signal generated upon analyzing theimages.
 6. The method according to claim 1, wherein the image sensingcondition detection step includes the step of analyzing an object imagesensed by the image sensing apparatus main body, and detecting changesin occlusion state of the object.
 7. The method according to claim 1,wherein the image sensing condition detection step includes the step ofanalyzing an object image sensed by the image sensing apparatus mainbody, and detecting an overlapping region area between time-serialobject images.
 8. The method according to claim 1, wherein the imagesensing condition detection step includes the step of analyzing anobject image sensed by the image sensing apparatus main body, anddetecting changes in distance image of the object.
 9. The methodaccording to claim 1, wherein the image analysis step includes the stepof performing an analysis calculation for acquiring a three-dimensionalshape and a surface image of the object using a plurality of images. 10.An image sensing method comprising: the image sensing step of sensingimages of an object; the analysis step of analyzing image informationobtained in the image sensing step; the image sensing conditiondetection step of detecting a relative relationship between the objectand an image sensing apparatus main body; and the control step ofcontrolling an image analysis operation in the analysis step, whereinthe control step includes the step of controlling the image analysisoperation in accordance with a detection result of the image sensingcondition detection step.
 11. The method according to claim 10, whereinthe analysis step includes the step of performing an analysiscalculation for acquiring a three-dimensional shape and a surface imageof the object using a plurality of images.
 12. The method according toclaim 10, wherein the image sensing condition detection step uses asensor for detecting an angle and translation movement of the imagesensing apparatus main body.
 13. The method according to claim 10,wherein the image sensing condition detection step includes the step ofanalyzing an object image and images around the object sensed by theimage sensing apparatus main body, and detecting an angle andtranslation movement of the image sensing apparatus main body on thebasis of changes in state of sensed images sensed in the image sensingstep.
 14. The method according to claim 10, wherein the image sensingcondition detection step includes the step of analyzing an object imageand images around the object sensed by the image sensing apparatus mainbody, and detecting changes in relative position relationship betweenthe object and the image sensing apparatus main body on the basis of anerror signal generated upon analyzing the images.
 15. The methodaccording to claim 10, wherein the image sensing condition detectionstep includes the step of analyzing an object image sensed by the imagesensing apparatus main body, and detecting changes in occlusion state ofthe object.
 16. The method according to claim 10, wherein the imagesensing condition detection step includes the step of analyzing anobject image sensed by the image sensing apparatus main body, anddetecting an overlapping region area between time-serial object images.17. The method according to claim 10, wherein the image sensingcondition detection step includes the step of analyzing an object imagesensed by the image sensing apparatus main body, and detecting changesin distance image of the object.
 18. The method according to claim 10,wherein the image sensing condition detection step includes the step ofstopping the image sensing step and the analysis step during a period inwhich neither storage processing nor analysis processing are performed.19. An image sensing apparatus comprising: image sensing means forsensing images of an object; storage means for storing image informationof the object; image sensing condition detection means for detecting arelative relationship between the object and an image sensing apparatusmain body; and control means for controlling said storage means, whereinthe control means controls said storage means in accordance with anoutput from said image sensing condition detection means.
 20. Theapparatus according to claim 19, wherein said control means controlssaid storage means to store information associated with the relativerelationship between the object and the image sensing apparatus mainbody together with sensed images sensed by said image sensing means. 21.The apparatus according to claim 19, wherein said image sensingcondition detection means comprises a sensor for detecting an angle andtranslation movement of the image sensing apparatus main body.
 22. Theapparatus according to claim 19, wherein said image sensing conditiondetection means analyzes an object image and images around the objectsensed by the image sensing apparatus main body, and detects an angleand translation movement of the image sensing apparatus main body on thebasis of changes in state of sensed images sensed by said image sensingmeans.
 23. The apparatus according to claim 19, wherein said imagesensing condition detection means analyzes an object image and imagesaround the object sensed by the image sensing apparatus main body, anddetects changes in relative position relationship between the object andthe image sensing apparatus main body on the basis of an error signalgenerated upon analyzing the images.
 24. The apparatus according toclaim 19, wherein said image sensing condition detection means analyzesan object image sensed by the image sensing apparatus main body, anddetects changes in occlusion state of the object.
 25. The apparatusaccording to claim 19, wherein said image sensing condition detectionmeans analyzes an object image sensed by the image sensing apparatusmain body, and detects an overlapping region area between time-serialobject images.
 26. The apparatus according to claim 19, wherein saidimage sensing condition detection means analyzes an object image sensedby the image sensing apparatus main body, and detects changes indistance image of the object.
 27. An image sensing apparatus comprising:image sensing means for sensing images of an object; image analysismeans for analyzing image information sensed by said image sensingmeans; image sensing condition detection means for detecting a relativerelationship between the object and an image sensing apparatus mainbody; and control means for controlling said image analysis means,wherein said control means controls said image analysis means inaccordance with an output from said image sensing condition detectionmeans.
 28. The apparatus according to claim 27, wherein said imageanalysis means performs an analysis calculation for acquiring athree-dimensional shape and a surface image of the object using aplurality of images.
 29. The apparatus according to claim 27, whereinsaid image sensing condition detection means comprises a sensor fordetecting an angle and translation movement of the image sensingapparatus main body.
 30. The apparatus according to claim 27, whereinsaid image sensing condition detection means analyzes an object imageand images around the object sensed by the image sensing apparatus mainbody, and detects an angle and translation movement of the image sensingapparatus main body on the basis of changes in state of sensed imagessensed by said image sensing means.
 31. The apparatus according to claim27, wherein said image sensing condition detection means analyzes anobject image and images around the object sensed by the image sensingapparatus main body, and detects changes in relative positionrelationship between the object and the image sensing apparatus mainbody on the basis of an error signal generated upon analyzing theimages.
 32. The apparatus according to claim 27, wherein said imagesensing condition detection means analyzes an object image sensed by theimage sensing apparatus main body, and detects changes in occlusionstate of the object.
 33. The apparatus according to claim 27, whereinsaid image sensing condition detection means analyzes an object imagesensed by the image sensing apparatus main body, and detects anoverlapping region area between time-serial object images.
 34. Theapparatus according to claim 27, wherein said image sensing conditiondetection means analyzes an object image sensed by the image sensingapparatus main body, and detects changes in distance image of theobject.
 35. The apparatus according to claim 27, wherein said imagesensing condition detection means stops operations of said image sensingmeans and said image analysis means during a period in which neitherstorage processing nor analysis processing are performed.